The overwhelming majority of accessibility platforms use automated scanning to identify potential accessibility issues on websites and other digital assets. These platforms run code-based rules against your digital assets and generate results of possible instances of WCAG non-conformance without the need for a human auditor. Therein lies the limitation: the issues are auto generated so they miss a lot.
Because scan results are extremely limited (reliably flagging only 7 of 55 WCAG 2.2 AA success criteria along with several partial flags), scan-based platforms cannot track progress towards full WCAG conformance, regardless of the standard.
Let’s look at the pros and cons of scan-based platforms in comparison to an audit-based platform like Accessibility Tracker.
| Detection Category | Platform Capability Description |
|---|---|
| Mostly Accurate (13%) | Technical, measurable criteria such as color contrast ratios, HTML validation, and missing alt attributes that produce consistent, reliable flags |
| Partially Detectable (45%) | Issues where platforms can identify some aspects but may miss crucial conformance components or generate false positives |
| Not Detectable (42%) | Requirements involving subjective evaluation of content quality, user experience, and contextual appropriateness that exceed automated capabilities |
| Continuous Monitoring | Ongoing automated scanning to identify new violations and monitor for regression after remediation efforts |
| Development Integration | Direct connection with code repositories and development workflows for real-time accessibility feedback |
Table of Contents
Technical Operation
Scan-based platforms function by analyzing HTML markup, CSS properties, and JavaScript behavior against predetermined accessibility rules. The scanning process examines page elements for patterns that may indicate WCAG violations, such as missing alternative text attributes, insufficient color contrast ratios, or improper heading hierarchies.
These platforms utilize various detection engines, including popular open-source libraries like aXe-core by Deque Systems, which many commercial platforms incorporate. The scanning algorithms apply binary logic to determine rule compliance, flagging elements that fail to meet specific technical criteria.
The automated nature of scanning enables rapid processing of large websites. Platforms can analyze thousands of pages within minutes, generating comprehensive reports that would require substantial time investment through manual evaluation methods.
Detection Categories and Reliability
The best way to think of scans is they can partially flag several WCAG criteria, but very few conclusively. Ultimately, this leads back to requiring a human expert review of all scan results. This means starting from an audit effectively preempts working from a scan because the audit is needed regardless of whether you fix all scan issues.
Here’s a breakdown of how many issues can detect.
Mostly Accurate Detection
Approximately 13% of WCAG 2.2 AA success criteria fall into the mostly accurate detection category. These criteria involve measurable, technical requirements where automated scanning produces consistent results with minimal false positives.
Examples include color contrast minimum requirements, where platforms can mathematically calculate ratios between text and background colors. HTML parsing validation represents another area of reliable detection, as platforms can identify syntax errors and malformed markup with high accuracy.
Page title presence and format checking also demonstrates reliable automated detection. Platforms can verify that title elements exist, identify duplicates across pages, and flag missing titles consistently.
Partially Detectable Issues
Nearly half of WCAG criteria (45%) fall into the partially detectable category, where platforms can identify some aspects of violations but may miss critical components or produce inconsistent results.
Alternative text for images exemplifies this limitation. While platforms reliably flag missing alt attributes, they cannot evaluate whether existing alternative text meaningfully describes image content or serves an appropriate purpose for screen reader users.
Keyboard accessibility presents similar challenges. Platforms may detect the presence of keyboard event handlers but cannot assess whether keyboard navigation follows logical patterns or provides complete functionality access.
Undetectable Requirements
Approximately 42% of WCAG criteria cannot be detected through automated scanning. These requirements involve human judgment about content quality, user experience, and contextual appropriateness.
Video caption accuracy represents a clear example of undetectable requirements. While platforms might identify the presence of caption elements, they cannot verify synchronization quality, content accuracy, or completeness of captions relative to audio content.
Navigation consistency across multiple pages requires human evaluation to assess logical organization and user experience coherence. Automated platforms cannot make subjective judgments about whether navigation patterns support user understanding and task completion.
Artificial Intelligence Integration
Modern scan-based platforms increasingly incorporate artificial intelligence capabilities to enhance detection accuracy and reduce false positive rates. AI-enhanced scanning can perform more sophisticated content analysis compared to traditional rule-based systems.
Natural language processing enables platforms to evaluate alternative text quality, assess link text clarity, and identify potentially confusing content patterns. Machine learning algorithms can recognize complex interaction patterns and suggest more contextually appropriate accessibility implementations.
However, AI integration introduces new difficulties alongside improvements. While traditional rule-based scanning produces deterministic results, AI systems may generate inconsistent outputs or suggest incorrect remediation approaches. The unpredictability requires additional human verification to validate AI-generated recommendations.
Comparison with Audit-Based Platforms
Audit-based platforms, such as Accessibility Tracker, operate from a fundamentally different foundation by utilizing comprehensive accessibility audit reports conducted by human experts. These platforms import detailed audit findings that cover all accessibility issues. This approach provides organizations with full visibility into accessibility issues that automated scanning cannot detect, though it requires greater upfront investment in professional auditing services.
While scan-based platforms excel at continuous monitoring and development integration, audit-based platforms provide complete visibility into accessibility status toward WCAG conformance. The distinction becomes significant for organizations pursuing comprehensive accessibility compliance rather than technical monitoring alone.
Audit-based platforms can track progress across all accessibility requirements because they begin with expert evaluation of actual user barriers. This comprehensive foundation enables accurate progress measurement toward conformance goals that scan-based platforms cannot provide due to detection limitations.
Development Workflow Integration
Scan-based platforms excel in development environment integration for accessibility practitioners who understand their narrow technical monitoring scope. These platforms connect directly with code repositories, continuous integration pipelines, and development tools, providing real-time feedback on the limited set of accessibility violations they can detect during the development process.
Accessibility-experienced developers can receive immediate notifications when code commits introduce technical issues that platforms can identify. This feedback loop helps prevent accumulation of detectable violations in production environments, though practitioners understand this covers only 13% of accessibility requirements.
Popular platforms offer integrations with GitHub, Bitbucket, Jenkins, and other development tools, making accessibility scanning useful for practitioners who employ them as narrow technical monitoring tools rather than accessibility assessment solutions.
Limitations and Considerations
Those evaluating scan-based platforms should understand their detection capabilities relative to their accessibility goals. While these platforms excel at quickly identifying accessibility issues and providing continuous monitoring and alerts, they cannot evaluate the majority of WCAG requirements, which involve human judgment about content appropriateness and user experience.
This creates a significant gap between what automated tools can measure and what comprehensive WCAG conformance (and legal compliance) requires. Organizations may find value in using scan-based platforms as part of a broader accessibility strategy that includes additional evaluation methods, particularly when immediate technical feedback during development is priorities.
Many consumers become focused on scan scores, but platforms showing high scores or clean results create false confidence among general users who interpret these metrics as complete accessibility validation. Organizations without accessibility expertise should use audit-based platforms like Accessibility Tracker that provide comprehensive visibility into actual accessibility status rather than the narrow technical subset that scanning can detect.
Organizations seeking complete accessibility assessment require audit-based approaches that cover all WCAG criteria. Scan-based platforms serve practitioners as technical monitoring tools but cannot support broader organizational accessibility objectives due to their inherent detection limitations.
Industry Applications
Large enterprise corporations should implement audit-based platforms for tracking full WCAG progress rather than relying on scan-based monitoring that covers only technical violations. Accessibility practitioners within these companies may use scan-based platforms as supplementary technical monitoring tools.
Educational institutions require comprehensive accessibility evaluation across diverse web content, making audit-based platforms the appropriate choice for institutional accessibility management. Scan-based platforms serve only practitioners who need specific technical monitoring capabilities.
Government agencies pursuing legal compliance and comprehensive user accessibility should utilize audit-based platforms that provide complete WCAG coverage. Scan-based platforms do offer value to accessibility practitioners who understand their role as limited technical monitoring tools within broader accessibility strategies that include comprehensive evaluation methods, but should not be used to work towards full WCAG conformance.
Organizations with strong development teams may find significant value in scan-based platforms for technical monitoring and regression prevention on some accessibility issues.
Insights
Scan-based accessibility platforms can serve specific organizational needs despite inherent limitations in comprehensive accessibility assessment. These platforms excel at technical monitoring, development integration, and rapid identification of measurable accessibility violations, making them valuable tools for organizations prioritizing continuous development oversight.
However, the fundamental limitation that automated scanning can reliably detect only 13% of WCAG criteria means organizations seeking full WCAG 2.1 AA or WCAG 2.2 AA conformance need to work from an audit and not a scan. Understanding these capabilities and limitations enables appropriate platform selection aligned with specific organizational accessibility objectives.
Frequently Asked Questions
What types of accessibility issues can scan-based platforms detect reliably?
Scan-based platforms reliably detect technical, measurable issues such as color contrast violations, missing alternative text attributes, HTML validation errors, improper heading hierarchies, and missing form labels. These represent approximately 13% of WCAG 2.2 AA success criteria.
How do scan-based platforms differ from comprehensive accessibility audits?
Scan-based platforms use automated rules to flag potential technical violations, while comprehensive audits involve human experts evaluating all aspects of user experience and WCAG conformance. These platforms can process content at scale, but miss the majority of issues.
Can multiple scan-based platforms improve detection coverage?
Using multiple platforms may identify additional technical issues through different detection algorithms, but all automated scanning faces the same fundamental limitations. No combination of scan-based platforms can detect the 42% of WCAG criteria requiring human evaluation of content quality and user experience.
What role does artificial intelligence play in modern scan-based platforms?
AI enhances scan-based platforms by improving content analysis, reducing false positives, and providing more contextual recommendations. However, AI cannot overcome the basic limitation that many accessibility requirements involve subjective human judgment about meaning, quality, and user experience appropriateness.
How should organizations integrate scan-based platforms into accessibility programs?
Organizations should use scan-based platforms for technical monitoring during development and ongoing regression testing while recognizing these tools cannot provide comprehensive accessibility assessment. Effective integration combines platform strengths with additional evaluation methods to address complete WCAG requirements.
Do scan-based platforms provide adequate compliance documentation?
Scan-based platforms cannot provide complete compliance documentation because they only assess a fraction of WCAG requirements. Organizations needing comprehensive compliance records for legal or regulatory purposes require additional evaluation methods beyond automated scanning capabilities.
Get Started with an Audit-Based Platform
You can try our audit-based platform for free at AccessibilityTracker.com.
